Scientific advances from the Human Genome Project have made DNA testing for breast-ovarian cancer susceptibility possible. Test results can be used to tailor cancer surveillance and risk reduction programs for women based on their genetic risk. These technological advances have raised many psychosocial and ethical-legal questions about the appropriate use of testing, the psychosocial consequences of testing, and the best ways to help individuals and families adjust to the health-related implications of the test results. Initial studies of responses to genetic testing have shown the need for further research in several areas, including factors related to psychological distress and the relationship between distress and participation in cancer surveillance. Suggested methods include exploring the processes whereby beliefs and experiences shape perceptions of genetic information. The project proposed here will adopt these recommendations in pursuit of the long-term goal of developing an independent research program to achieve adherence to cancer surveillance and risk reduction recommendations. To accomplish this, the candidate will pursue a career development program consisting of training in: (a) clinical genetics and the psychosocial aspects of cancer risk notification, surveillance, and risk reduction; (b) measuring and modeling cognitive, affective, and behavioral processes in cancer risk notification, surveillance, and risk reduction, with a focus on genetic testing; and (c) testing psychosocial interventions and conducting clinical trials. This training will be applied in two research studies; (a) Study 1, a longitudinal study to describe relationships between mental representations of genetic predisposition to breast cancer, coping, and breast cancer surveillance behaviors in women (N=200) who participate in genetic testing and (b) Study 2, design and pilot test interventions from effectiveness in achieving adherence to breast cancer surveillance and self-regulation of psychological distress in women (N=60) eligible for genetic testing for breast cancer predisposition. Findings will be used to develop an R01 proposal to fully test the interventions developed in Study 2. The Common Sense Model of Illness will provide the theoretical basis for both studies, because it emphasizes how health-related experiences, in the form of mental representations, affect health behaviors. Structural equation modeling will be used for measurement assessment and hypothesis testing. Traditional psychometric methods will also be used to estimate instrument reliability and validity. Changes over time in responses to genetic testing will be measured with repeated measures ANOVA. Qualitative data will be analyzed with content analysis and nonparametric statistics.